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import streamlit as st |
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import uuid |
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import json |
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from components import PersonalIndexClient, LLMClient, WebSearcher |
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st.title("Talk with Mingzhe") |
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llm_client = LLMClient(api_key=st.secrets["OPENAI_API_KEY"], model_name="gpt-4-turbo-preview") |
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pinecone_client = PersonalIndexClient(index_token=st.secrets["PINECONE_API_KEY"], embedding_token=st.secrets["OPENAI_API_KEY"], embedding_model_name='text-embedding-3-large', index_name='mingzhe') |
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web_searcher = WebSearcher(you_api_key=st.secrets["YOU_API_KEY"], bing_api_key=st.secrets["BING_API_KEY"]) |
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if "messages" not in st.session_state: |
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st.session_state.messages = [] |
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st.session_state['sid'] = uuid.uuid1().hex |
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st.session_state['user'] = 'default' |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"]): |
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st.markdown(message["content"]) |
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if prompt := st.chat_input("What's up?"): |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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with st.chat_message("user"): |
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st.markdown(prompt) |
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with st.chat_message("assistant"): |
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print(f"Prompt: {prompt}") |
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memory = pinecone_client.query_conversation(messages=st.session_state.messages[:-5], user=st.session_state['user'], top_k=3) |
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print(f"Memory: {memory}") |
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web_query = llm_client.web_query_generator(query=prompt, history=st.session_state.messages) |
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print(f"Web Query: {web_query}") |
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web_result = web_searcher.query_bing(query=web_query) if web_query != 'None' else "None" |
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print(f"Web Result: {web_result}") |
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stream = llm_client.response_generate(prompt, st.session_state.messages, memory, web_result) |
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response = st.write_stream(stream) |
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print(f"Response: {response}") |
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st.session_state.messages.append({"role": "assistant", "content": response}) |
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pinecone_client.update_conversation(sid=st.session_state['sid'], messages=st.session_state.messages, user=st.session_state['user']) |
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print("\n===========================\n") |
